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America’s biggest obstacle in the technology race with China may no be Beijing, but growing resistance to new data centers and the power needed to run them, according to Palantir’s chief technology officer.
“The proximate issues are definitely going to be power and backlash against data centers,” Shyam Sankar said in an interview with Fox News Digital at Palantir’s American Builder Summit.
Sankar, whose company builds software for the Pentagon, intelligence agencies and major manufacturers, argued the U.S. risks slowing its own technological progress more than falling behind Beijing.
“The only threat to AI generating prosperity for America is suicide, not homicide.”
The U.S. and China are pouring billions into the race to dominate artificial intelligence, viewing the technology as central to economic growth, military power and geopolitical influence. Winning that race depends on an enormous buildout of data centers, power generation and transmission infrastructure to support increasingly capable systems. But those projects have drawn growing resistance from communities worried about electricity demand, water use and whether the benefits will outweigh the costs.
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Companies have raced to build new data centers to support a wave of new computing infrastructure, fueling a nationwide expansion that has also sparked growing local opposition. The issue has spilled into the 2026 midterm campaigns, with candidates in battleground states such as Pennsylvania running ads focused on the economic and environmental effects of the projects.
Residents have raised concerns about electricity demand, water consumption, noise, traffic and whether utility customers will ultimately bear the cost of expanding the power grid. Some projects have been delayed or canceled, while lawmakers in several states have proposed restrictions or moratoriums on new facilities.
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Some developers have responded by pairing new data centers with dedicated power generation rather than relying entirely on the electric grid.
Sankar argues those debates risk slowing the industrial gains the technology can already deliver. He pointed to one submarine-parts manufacturer that cut production planning from two weeks to less than an hour, freeing enough capacity to add a third shift.
“There is no one on that shift who thinks, ‘Hey, I got my job because of AI,’ but that’s actually what happened,” he said.
The summit itself appeared designed to counter one of the AI industry’s biggest public relations challenges: fears that the technology will replace jobs. Rather than showcasing increasingly capable AI models, Palantir filled the stage with factory workers, healthcare workers and military personnel demonstrating software they had built to solve problems in their own workplaces.
Sankar argued the AI industry has become overly focused on pursuing artificial general intelligence, or AGI, rather than deploying today’s AI systems across the economy.
Artificial general intelligence, or AGI, refers to a still-theoretical system capable of performing a broad range of intellectual tasks at or beyond human level, rather than excelling mainly at narrower tasks such as writing, coding or image analysis.
He compared the current moment to the early days of electricity, arguing that while the technology already exists, businesses have yet to reorganize themselves around it.
“The AI we have is powerful enough that it should have created more prosperity and value,” he said. “The only reason it hasn’t yet is not a failing of the technology, it’s a lack of our national will to push and invest in diffusing the technology through our economy.”
“We shouldn’t lose the plot in pining away for a machine god,” he added.
The summit brought together a cohort of Palantir’s American Tech Fellowship, where workers from industries including manufacturing, healthcare and defense demonstrated AI applications they had built for use in their jobs.
The demonstrations were intended to illustrate Sankar’s contention: that AI will make workers more productive than ever rather than replace them.
That runs against much of the public sentiment, where workers across industries have begun to wonder how long until their jobs will be done by a machine.
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“How many people have actually, at the front line, have experienced AI and how it’s changed their job versus how many people are imbibing the fear-mongering from the social media feed, which is partially a Chinese Psyop as well.”
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